| dc.creator |
Mulungu, Deogratias M. M. |
|
| dc.creator |
Munishi, Subira E. |
|
| dc.date |
2016-07-15T12:59:40Z |
|
| dc.date |
2016-07-15T12:59:40Z |
|
| dc.date |
2007 |
|
| dc.date.accessioned |
2018-03-27T08:41:13Z |
|
| dc.date.available |
2018-03-27T08:41:13Z |
|
| dc.identifier |
Mulungu, D.M. and Munishi, S.E., 2007. Simiyu River catchment parameterization using SWAT model. Physics and Chemistry of the Earth, Parts A/B/C, 32(15), pp.1032-1039. |
|
| dc.identifier |
http://hdl.handle.net/20.500.11810/3234 |
|
| dc.identifier |
10.1016/j.pce.2007.07.053 |
|
| dc.identifier.uri |
http://hdl.handle.net/20.500.11810/3234 |
|
| dc.description |
The paper presents advances in hydrologic modelling of the Simiyu River catchment using the soil and water assessment tool (SWAT). In this study, the SWAT model set-up and subsequent application to the catchment was based on high-resolution data such as land use from 30m LandSat TM Satellite, 90m Digital Elevation Model and Soil from Soil and Terrain Database for Southern Africa (SOTERSAF).The land use data were reclassified based on some ground truth maps using IDRISI Kilimanjaro software. The Soil data were also reclassified manually to represent different soil hydrologic groups, which are important for the SWAT model set-up and simulations.The SWAT application first involved analysis of parameter sensitivity, which was then used for model auto-calibration that followed hierarchy of sensitive model parameters. The analysis of sensitive parameters and auto-calibration was achieved by sensitivity analysis and auto-calibration options, which are new in the recent version of SWAT, SWAT 2005.The paper discusses the results of sensitivity and auto-calibration analyses, and present optimum model parameters, which are important for operation and water/land management studies (e.g. rain-fed agriculture and erosion/sediment and pollutant transport) in the catchment using SWAT. The river discharge estimates from this and a previous study were compared so as to evaluate performances of the recent hydrologic simulations in the catchment.Results showed that surface water model parameters are the most sensitive and have more physical meaning especially CN2 (the most sensitive) and SOL_K. Simulation results showed more or less same estimate of river flow at Ndagalu gauging station. The model efficiencies (R2%) in this and in the pervious study during calibration and validation periods were, respectively, 13.73, 14.22 and 40.54, 36.17. The low level of model performance achieved in these studies showed that other factors than the spatial land data are greatly important for improvement of flow estimation by SWAT in Simiyu. |
|
| dc.language |
en |
|
| dc.publisher |
Elsevier |
|
| dc.title |
Simiyu River Catchment Parameterization Using SWAT Model |
|
| dc.type |
Journal Article, Peer Reviewed |
|